Advanced MRI prediction model for anatomical site identification in uterine carcinoma: enhancing diagnostic accuracy

Abstract

Aim: The uterine carcinoma is the most commonly diagnosed malignancy in the female pelvis. Accurate identification of tumour origin is crucial for determining appropriate treatment approaches. This study aims to develop a prediction model using multiple MRI parameters to accurately diagnose uterine cancer with an indistinctive origin and those involving both the endometrium and cervix prior to treatment.

Material and methods: This prospective cohort study included patients who were newly diagnosed with uterine carcinoma who underwent MRI and were considered for hysterectomy within 6 months after MRI.

Results: A total of 78 patients with uterine carcinoma were enrolled. Certain imaging features were found to be consistent with cervical carcinoma, included parametrial, vaginal, stromal invasion, and peripheral rim enhancement. Cervical cancer appeared hyperintense compared to the myometrium unlike endometrial cancer.

Discussion: The study found that certain morphologic features were reliable indicators for detecting cervical carcinoma.